Although associations have been established between retailer densities and health-risk behaviors (smoking, drinking, poor-quality diet and obesity), little is known about the causal mechanisms linking retailer density to individual behavior; and even less is known about the possible effects of different policy approaches to reduce retailer density. Prospective, experimental studies in this area are difficult, if not impossible to conduct. Changes in retailer density are likely to be systemic in nature, and have complex, non-linear effects. This study will use dynamic systems modeling to examine the interplay between retailer density reductions and patterns of tobacco purchasing. The study has two primary aims. First, agent-based modeling will be used to build Tobacco Town, a simulation of a realistic community that will be used to model tobacco retailer density and individual tobacco purchasing. Second, after the model is built it will be used as a retail policy laboratory o explore and compare the potential effects on behavior of a suite of real-world retailer reduction policy approaches, including policies that reduce density through location-based zoning, type of retailer zoning, increased licensing fees, or cap and winnow policies. The effects of the retailer density policies on vulnerable populations will also be examined, particularly for low-income residents and minorities. Results of this modeling study will be useful for health policy and tobacco control scientists and evaluators as they develop evidence- based policies to counter the effects of tobacco industry activities at the point of sale. The results will also be of interet to implementation scientists--the development of the density policy laboratory represents the first stage of a line of work that will help develop dynamic systems approaches to studying the effects of public health policy implementation.